As the amount of data that is maintained by an organization increases, effective data governance policies for each specific type of data can become increasingly complex. Different types of data can require different security, access control, encryption, and archiving requirements. With hundreds of different types of data within an organization, assessing the overall quality of data governance practices often becomes a tedious and lengthy process.
From structured to unstructured data including customer and employee data, metadata, trade secrets, e-mail, video and audio; organizations often struggle to find a way to govern data in alignment with business requirements without obstructing the free flow of information and innovation. For many organizations, data is spread across multiple, complex silos that are isolated from each other. There can be scores of redundant copies of data, and the business processes that use such data are often just as redundant and tangled. In many situations, there is little cross-organizational collaboration, with few defined governance and stewardship structures, roles and responsibilities. However, such organizations often want to leverage information for maximum performance and profit. They may want to assess the value of data as a balance sheet asset, and to calculate risk in all aspects of their operations as a competitive advantage in decision-making.